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Fuzzy Logic Evaluation of Knee Flexion Angle During Gait
In this paper, we propose a method for quantitative gait analysis with videos. First, the joint position coordinates are estimated with the gait video. Next, by tracking the person and analyzing the knee joint, we obtain the time series data of the subject's knee flexion angle. Finally, based o...
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creator | Hayashi, Kohei Harada, Risa Naomiyagi Hata, Yutaka Saji, Yoshiaki Sakai, Yoshitada |
description | In this paper, we propose a method for quantitative gait analysis with videos. First, the joint position coordinates are estimated with the gait video. Next, by tracking the person and analyzing the knee joint, we obtain the time series data of the subject's knee flexion angle. Finally, based on fuzzy logic, we evaluate how close the subject's gait was to a normal gait. As a result, the mean value of fuzzy degree is 0.70±0.031(range: 0.64-0.74) for healthy adults and 0.18±0.043(range: 0.11-0.22) for patients. This system enables quantitative evaluation of gait more easily than existing methods. |
doi_str_mv | 10.1109/ICMLC58545.2023.10327930 |
format | conference_proceeding |
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This system enables quantitative evaluation of gait more easily than existing methods.</description><subject>3D Pose Estimation</subject><subject>Fuzzy logic</subject><subject>Gait Analysis</subject><subject>Knee</subject><subject>Knee Flexion Angle</subject><subject>Medical services</subject><subject>Performance evaluation</subject><subject>Pose estimation</subject><subject>Three-dimensional displays</subject><subject>Time series analysis</subject><issn>2160-1348</issn><isbn>9798350303780</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2023</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><recordid>eNo1j81KxDAURqMgOIx9Axd5gdabe5M0WQ51Og5W3Oh6iG1SIrWV_ogzT6-ifpvD2Rz4GOMCMiHA3uyLh6pQRkmVISBlAghzS3DGEptbQwoIKDdwzlYoNKSCpLlkyTS9wvdyKY0VK2bK5XQ68mpoY823H65b3ByHng-B3_fe87Lznz--6dvO89tljH3Ldy7OV-wiuG7yyR_X7LncPhV3afW42xebKo1C2DnVShChBmGaOg-kMEf00oXaauM9OHIBiUxovESNdZANIpqgm-CMdS9Ia3b9243e-8P7GN_ceDz8n6Uv-c1H1Q</recordid><startdate>20230709</startdate><enddate>20230709</enddate><creator>Hayashi, Kohei</creator><creator>Harada, Risa</creator><creator>Naomiyagi</creator><creator>Hata, Yutaka</creator><creator>Saji, Yoshiaki</creator><creator>Sakai, Yoshitada</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>20230709</creationdate><title>Fuzzy Logic Evaluation of Knee Flexion Angle During Gait</title><author>Hayashi, Kohei ; Harada, Risa ; Naomiyagi ; Hata, Yutaka ; Saji, Yoshiaki ; Sakai, Yoshitada</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i119t-6513326018dc7f352722e4afc968ee0a3af2338fde4262cf4d2228f6dfa89ab23</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2023</creationdate><topic>3D Pose Estimation</topic><topic>Fuzzy logic</topic><topic>Gait Analysis</topic><topic>Knee</topic><topic>Knee Flexion Angle</topic><topic>Medical services</topic><topic>Performance evaluation</topic><topic>Pose estimation</topic><topic>Three-dimensional displays</topic><topic>Time series analysis</topic><toplevel>online_resources</toplevel><creatorcontrib>Hayashi, Kohei</creatorcontrib><creatorcontrib>Harada, Risa</creatorcontrib><creatorcontrib>Naomiyagi</creatorcontrib><creatorcontrib>Hata, Yutaka</creatorcontrib><creatorcontrib>Saji, Yoshiaki</creatorcontrib><creatorcontrib>Sakai, Yoshitada</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Xplore</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Hayashi, Kohei</au><au>Harada, Risa</au><au>Naomiyagi</au><au>Hata, Yutaka</au><au>Saji, Yoshiaki</au><au>Sakai, Yoshitada</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Fuzzy Logic Evaluation of Knee Flexion Angle During Gait</atitle><btitle>2023 International Conference on Machine Learning and Cybernetics (ICMLC)</btitle><stitle>ICMLC</stitle><date>2023-07-09</date><risdate>2023</risdate><spage>370</spage><epage>375</epage><pages>370-375</pages><eissn>2160-1348</eissn><eisbn>9798350303780</eisbn><abstract>In this paper, we propose a method for quantitative gait analysis with videos. First, the joint position coordinates are estimated with the gait video. Next, by tracking the person and analyzing the knee joint, we obtain the time series data of the subject's knee flexion angle. Finally, based on fuzzy logic, we evaluate how close the subject's gait was to a normal gait. As a result, the mean value of fuzzy degree is 0.70±0.031(range: 0.64-0.74) for healthy adults and 0.18±0.043(range: 0.11-0.22) for patients. This system enables quantitative evaluation of gait more easily than existing methods.</abstract><pub>IEEE</pub><doi>10.1109/ICMLC58545.2023.10327930</doi><tpages>6</tpages></addata></record> |
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subjects | 3D Pose Estimation Fuzzy logic Gait Analysis Knee Knee Flexion Angle Medical services Performance evaluation Pose estimation Three-dimensional displays Time series analysis |
title | Fuzzy Logic Evaluation of Knee Flexion Angle During Gait |
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